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Journal of Inforamtion Science and Engineering, Vol.12 No.1, pp.1-23 (March 1996)
Least-Squares Algorithms for Motion and
Shape Recovery Under Perspective

Chiou-Shann Fuh and Petros Maragos*
Department of Computer Science and Information Engineering
National Taiwan University
Taipei, Taiwan, R.O.C.
*School of Electrical Engineering
Georgia Institute of Technology
Atlanta, GA 30332, USA

This paper presents an algorithm for 3-D motion and shape recovery using two perspective views and their relative 2-D displacement field. The 2-D displacement vectors are estimated as parameters of a 2-D affine model that generalizes standard block matching by allowing affine shape deformations of image blocks and affine intensity transformations. The matching block size is effectively found via morphological size histograms. The parameters of the rigid body motion are estimated using a least-squares algorithm that requires solving a system of linear equations with rank three. Some stabilization of the recovered motion parameters under noise is achieved through a simple form of maximum a posteriori estimation. A multi-scale search in the parameter space is also used to improve accuracy without high computational cost. Experiments on applying this algorithm to various real world image sequences demonstrate that it can estimate dense displacement fields and recover motion parameters and object shape with relatively small errors.

Keywords: computer vision, motion analysis, correspondence

Received August 18, 1994; revised May 19, 1995.
Communicated by Zen Chen.